Data Science for Web3
A comprehensive guide to understandind and applying data science principles in Web3 technologies, with real-world examples.
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"With Data Science for Web3, you can build up your analytics skills for blockchain from the foundation until real use cases."
- Rodolfo Lima
ABOUT THE BOOK
A comprehensive guide to extracting value from Blockchain data.
Key Features
Practical Guidance: From fundamental blockchain concepts to advanced data science techniques, this book provides step-by-step instructions to navigate the complexities of Web3 data.
Industry Best Practices: Discover the latest tools, resources, and strategies essential for success in the rapidly evolving landscape of Web3 data analysis.
Real-World Examples: Learn from industry leaders from Dune Analytics, Flipside Analytics, Dragonfly and Sovryn through exclusive interviews, gaining valuable insights into their professional journeys and innovative approaches to Blockchain data.
What do we cover?
- Blockchain Essentials: Gain a solid understanding of blockchain transactions and blocks and tokens.
- Data Sourcing: Learn to identify and leverage reliable sources of both on-chain and off-chain data to build robust datasets.
- NFTs and DeFi: Master the creation and querying of NFT- and DeFi-specific datasets, unlocking new opportunities in the decentralized finance landscape.
- Machine Learning Applications: Explore diverse machine learning use cases in the Web3 space.
The Author
Gabriela Castillo Areco is data lead at Rootstock Labs, core contributor of the first Bitcoin sidechain called Rootstock. She holds an M.Sc. in big data science from the TECNUM School of Engineering, University of Navarra.
With extensive experience in both the business and data facets of blockchain technology, Gabriela has undertaken roles as a data scientist, machine learning analyst, and blockchain consultant in both large corporations and small ventures.
She served as a professor of new crypto businesses at Torcuato di Tella University and collaborated with Crypto Resources academy in building their “Learn to Earn” segment.
Gabriela Castillo Areco
INDEX
Blockchain analytics
1. Where Data and Web3 Meet.
2. Working with On-Chain Data.
3. Hands on with Off-chain data.
4. Digital uniqueness – NFTs datasets (Games, Art, ENS).
5. Exploring analytics on DEFI.
Machine Learning
6. Preparing and Exploring our Data.
7. Machine Learning and Deep Learning Primer.
8. Sentiment analysis: NLP and crypto news.
9. Generative art for NFTs.
10. A primer on security and fraud detection.
11. Price prediction with time series.
12. Marketing discovery with Graphs.
Bonus
13. Building experience with crypto data – Buidl
14. Insights from Web3 data leaders.
blog
The case for Web3 credit scoring – unlocking value
How Web3 Credit Scoring Will Unlock Significant ValueCurrent Situation: Overcollateralized LoansWell-established on-chain lending protocols predominantly adhere to an overcollateralized framework,...
Decoding Web3 Credit Scoring: Cracking RociFi’s ML Model
While searching for models that integrate Web3 credit scoring, I came across RociFi, a protocol that has gradually evolved from a scoring model integrated within a loan protocol to a model offering...